Handwritten numeral recognition using flexible matching based on learning of stroke statistics

Author

KOBAYASHI, Takashi ; Nakamura, Kaori ; MURAMATSU, Hirokazu ; Sugiyama, Takahiro ; Abe, Keiichi

Author_Institution

Dept. of Comput. Sci., Shizuoka Univ., Japan

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

612

Lastpage

616

Abstract

The purpose of this study is to learn shapes and structures of a given learning set of handwritten numerals and to develop a flexible matching method for recognition based on the learning. First, this paper proposes a method of how to obtain a set of standard character patterns and the ranges of variations varying statistically from the given learning character samples. Then the recognition is made as follows: each standard pattern is deformed to match with the input character; and the matching is evaluated by the energy of deformation; and the closeness of the standard pattern to the input

Keywords

handwritten character recognition; learning (artificial intelligence); pattern matching; statistical analysis; flexible pattern matching; handwritten character recognition; handwritten numeral recognition; learning; standard patterns; stroke statistics; Character recognition; Computer science; Handwriting recognition; Humans; Impedance matching; Neural networks; Pattern matching; Pattern recognition; Shape; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7695-1263-1

Type

conf

DOI

10.1109/ICDAR.2001.953862

Filename

953862